Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationTue, 16 Nov 2010 19:58:46 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/16/t1289937452a09rz2egojk17xi.htm/, Retrieved Sun, 05 May 2024 08:21:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=96360, Retrieved Sun, 05 May 2024 08:21:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
-  MPD  [Bivariate Data Series] [mini tutorial] [2010-11-16 19:47:52] [bd591a1ebb67d263a02e7adae3fa1a4d]
- RMPD      [Central Tendency] [totale productie ...] [2010-11-16 19:58:46] [09489ba95453d3f5c9e6f2eaeda915af] [Current]
Feedback Forum

Post a new message
Dataseries X:
94,6
95,9
104,7
102,8
98,1
113,9
80,9
95,7
113,2
105,9
108,8
102,3
99
100,7
115,5
100,7
109,9
114,6
85,4
100,5
114,8
116,5
112,9
102
106
105,3
118,8
106,1
109,3
117,2
92,5
104,2
112,5
122,4
113,3
100
110,7
112,8
109,8
117,3
109,1
115,9
96
99,8
116,8
115,7
99,4
94,3
91
93,2
103,1
94,1
91,8
102,7
82,6
89,1
104,5
105,1
95,1
88,7
86,3
91,8
111,5
99,7
97,5
111,7
86,2
95,4




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96360&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96360&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96360&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean103.1705882352941.2066196165890685.5038214337527
Geometric Mean102.687720580833
Harmonic Mean102.195149889976
Quadratic Mean103.642258017948
Winsorized Mean ( 1 / 22 )103.1426470588241.1884399217705186.7882718927548
Winsorized Mean ( 2 / 22 )103.1808823529411.1600332587209088.9464862987742
Winsorized Mean ( 3 / 22 )103.2117647058821.1513029024483489.6477933707924
Winsorized Mean ( 4 / 22 )103.1941176470591.1457883376221890.0638575718221
Winsorized Mean ( 5 / 22 )103.3485294117651.1049622541852393.5312758606144
Winsorized Mean ( 6 / 22 )103.3308823529411.0887630563027594.90667574985
Winsorized Mean ( 7 / 22 )103.5058823529411.0486872146854398.7004331734787
Winsorized Mean ( 8 / 22 )103.5764705882351.02818514653411100.737178452129
Winsorized Mean ( 9 / 22 )103.4838235294121.0124371674195102.212588454424
Winsorized Mean ( 10 / 22 )103.5573529411760.99008765093063104.594126432986
Winsorized Mean ( 11 / 22 )103.5573529411760.952857898435739108.680793968525
Winsorized Mean ( 12 / 22 )103.6102941176470.91059546867767113.783010877603
Winsorized Mean ( 13 / 22 )103.6294117647060.901630215154422114.935602226859
Winsorized Mean ( 14 / 22 )103.6294117647060.88240795848376117.439343977328
Winsorized Mean ( 15 / 22 )103.7176470588240.862294092881539120.281059461081
Winsorized Mean ( 16 / 22 )103.7176470588240.840765937996706123.360905064674
Winsorized Mean ( 17 / 22 )103.5926470588240.798952112699262129.660646003971
Winsorized Mean ( 18 / 22 )103.5926470588240.783169973311035132.273517357747
Winsorized Mean ( 19 / 22 )103.3970588235290.745866486427765138.626765922594
Winsorized Mean ( 20 / 22 )103.6029411764710.647813132843446159.927201107712
Winsorized Mean ( 21 / 22 )103.7573529411760.617616407743162167.996432154899
Winsorized Mean ( 22 / 22 )103.8867647058820.554947831556828187.200956195184
Trimmed Mean ( 1 / 22 )103.2166666666671.1594681349077189.0207014398741
Trimmed Mean ( 2 / 22 )103.29531251.1245643549967591.8536249535476
Trimmed Mean ( 3 / 22 )103.3580645161291.1007462215456193.898177884271
Trimmed Mean ( 4 / 22 )103.4133333333331.0757009714775196.1357627029857
Trimmed Mean ( 5 / 22 )103.4775862068971.0469817857393698.8341799411747
Trimmed Mean ( 6 / 22 )103.5089285714291.02500008484546100.984312198407
Trimmed Mean ( 7 / 22 )103.5462962962961.00221527152351103.317420157539
Trimmed Mean ( 8 / 22 )103.5538461538460.984336074636877105.201718012872
Trimmed Mean ( 9 / 22 )103.550.966522273991887107.136692848601
Trimmed Mean ( 10 / 22 )103.5604166666670.947204451479136109.332696341269
Trimmed Mean ( 11 / 22 )103.5608695652170.927275778649608111.682923192530
Trimmed Mean ( 12 / 22 )103.5613636363640.90966861929213113.845153542783
Trimmed Mean ( 13 / 22 )103.5547619047620.895615869708537115.624081045440
Trimmed Mean ( 14 / 22 )103.5450.877999985398049117.932803783655
Trimmed Mean ( 15 / 22 )103.5342105263160.857999561617178120.669304691919
Trimmed Mean ( 16 / 22 )103.5111111111110.834777584462042123.998431483779
Trimmed Mean ( 17 / 22 )103.4852941176470.807398193147852128.171322398162
Trimmed Mean ( 18 / 22 )103.4718750.7798655071058132.679127435703
Trimmed Mean ( 19 / 22 )103.4566666666670.743967051138743139.060817960032
Trimmed Mean ( 20 / 22 )103.4642857142860.702851604486288147.206444509588
Trimmed Mean ( 21 / 22 )103.4461538461540.675351322116144153.173837761975
Trimmed Mean ( 22 / 22 )103.4041666666670.641936584486673161.081591492958
Median102.95
Midrange101.65
Midmean - Weighted Average at Xnp103.254285714286
Midmean - Weighted Average at X(n+1)p103.485294117647
Midmean - Empirical Distribution Function103.254285714286
Midmean - Empirical Distribution Function - Averaging103.485294117647
Midmean - Empirical Distribution Function - Interpolation103.485294117647
Midmean - Closest Observation103.254285714286
Midmean - True Basic - Statistics Graphics Toolkit103.485294117647
Midmean - MS Excel (old versions)103.511111111111
Number of observations68

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 103.170588235294 & 1.20661961658906 & 85.5038214337527 \tabularnewline
Geometric Mean & 102.687720580833 &  &  \tabularnewline
Harmonic Mean & 102.195149889976 &  &  \tabularnewline
Quadratic Mean & 103.642258017948 &  &  \tabularnewline
Winsorized Mean ( 1 / 22 ) & 103.142647058824 & 1.18843992177051 & 86.7882718927548 \tabularnewline
Winsorized Mean ( 2 / 22 ) & 103.180882352941 & 1.16003325872090 & 88.9464862987742 \tabularnewline
Winsorized Mean ( 3 / 22 ) & 103.211764705882 & 1.15130290244834 & 89.6477933707924 \tabularnewline
Winsorized Mean ( 4 / 22 ) & 103.194117647059 & 1.14578833762218 & 90.0638575718221 \tabularnewline
Winsorized Mean ( 5 / 22 ) & 103.348529411765 & 1.10496225418523 & 93.5312758606144 \tabularnewline
Winsorized Mean ( 6 / 22 ) & 103.330882352941 & 1.08876305630275 & 94.90667574985 \tabularnewline
Winsorized Mean ( 7 / 22 ) & 103.505882352941 & 1.04868721468543 & 98.7004331734787 \tabularnewline
Winsorized Mean ( 8 / 22 ) & 103.576470588235 & 1.02818514653411 & 100.737178452129 \tabularnewline
Winsorized Mean ( 9 / 22 ) & 103.483823529412 & 1.0124371674195 & 102.212588454424 \tabularnewline
Winsorized Mean ( 10 / 22 ) & 103.557352941176 & 0.99008765093063 & 104.594126432986 \tabularnewline
Winsorized Mean ( 11 / 22 ) & 103.557352941176 & 0.952857898435739 & 108.680793968525 \tabularnewline
Winsorized Mean ( 12 / 22 ) & 103.610294117647 & 0.91059546867767 & 113.783010877603 \tabularnewline
Winsorized Mean ( 13 / 22 ) & 103.629411764706 & 0.901630215154422 & 114.935602226859 \tabularnewline
Winsorized Mean ( 14 / 22 ) & 103.629411764706 & 0.88240795848376 & 117.439343977328 \tabularnewline
Winsorized Mean ( 15 / 22 ) & 103.717647058824 & 0.862294092881539 & 120.281059461081 \tabularnewline
Winsorized Mean ( 16 / 22 ) & 103.717647058824 & 0.840765937996706 & 123.360905064674 \tabularnewline
Winsorized Mean ( 17 / 22 ) & 103.592647058824 & 0.798952112699262 & 129.660646003971 \tabularnewline
Winsorized Mean ( 18 / 22 ) & 103.592647058824 & 0.783169973311035 & 132.273517357747 \tabularnewline
Winsorized Mean ( 19 / 22 ) & 103.397058823529 & 0.745866486427765 & 138.626765922594 \tabularnewline
Winsorized Mean ( 20 / 22 ) & 103.602941176471 & 0.647813132843446 & 159.927201107712 \tabularnewline
Winsorized Mean ( 21 / 22 ) & 103.757352941176 & 0.617616407743162 & 167.996432154899 \tabularnewline
Winsorized Mean ( 22 / 22 ) & 103.886764705882 & 0.554947831556828 & 187.200956195184 \tabularnewline
Trimmed Mean ( 1 / 22 ) & 103.216666666667 & 1.15946813490771 & 89.0207014398741 \tabularnewline
Trimmed Mean ( 2 / 22 ) & 103.2953125 & 1.12456435499675 & 91.8536249535476 \tabularnewline
Trimmed Mean ( 3 / 22 ) & 103.358064516129 & 1.10074622154561 & 93.898177884271 \tabularnewline
Trimmed Mean ( 4 / 22 ) & 103.413333333333 & 1.07570097147751 & 96.1357627029857 \tabularnewline
Trimmed Mean ( 5 / 22 ) & 103.477586206897 & 1.04698178573936 & 98.8341799411747 \tabularnewline
Trimmed Mean ( 6 / 22 ) & 103.508928571429 & 1.02500008484546 & 100.984312198407 \tabularnewline
Trimmed Mean ( 7 / 22 ) & 103.546296296296 & 1.00221527152351 & 103.317420157539 \tabularnewline
Trimmed Mean ( 8 / 22 ) & 103.553846153846 & 0.984336074636877 & 105.201718012872 \tabularnewline
Trimmed Mean ( 9 / 22 ) & 103.55 & 0.966522273991887 & 107.136692848601 \tabularnewline
Trimmed Mean ( 10 / 22 ) & 103.560416666667 & 0.947204451479136 & 109.332696341269 \tabularnewline
Trimmed Mean ( 11 / 22 ) & 103.560869565217 & 0.927275778649608 & 111.682923192530 \tabularnewline
Trimmed Mean ( 12 / 22 ) & 103.561363636364 & 0.90966861929213 & 113.845153542783 \tabularnewline
Trimmed Mean ( 13 / 22 ) & 103.554761904762 & 0.895615869708537 & 115.624081045440 \tabularnewline
Trimmed Mean ( 14 / 22 ) & 103.545 & 0.877999985398049 & 117.932803783655 \tabularnewline
Trimmed Mean ( 15 / 22 ) & 103.534210526316 & 0.857999561617178 & 120.669304691919 \tabularnewline
Trimmed Mean ( 16 / 22 ) & 103.511111111111 & 0.834777584462042 & 123.998431483779 \tabularnewline
Trimmed Mean ( 17 / 22 ) & 103.485294117647 & 0.807398193147852 & 128.171322398162 \tabularnewline
Trimmed Mean ( 18 / 22 ) & 103.471875 & 0.7798655071058 & 132.679127435703 \tabularnewline
Trimmed Mean ( 19 / 22 ) & 103.456666666667 & 0.743967051138743 & 139.060817960032 \tabularnewline
Trimmed Mean ( 20 / 22 ) & 103.464285714286 & 0.702851604486288 & 147.206444509588 \tabularnewline
Trimmed Mean ( 21 / 22 ) & 103.446153846154 & 0.675351322116144 & 153.173837761975 \tabularnewline
Trimmed Mean ( 22 / 22 ) & 103.404166666667 & 0.641936584486673 & 161.081591492958 \tabularnewline
Median & 102.95 &  &  \tabularnewline
Midrange & 101.65 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 103.254285714286 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 103.485294117647 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 103.254285714286 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 103.485294117647 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 103.485294117647 &  &  \tabularnewline
Midmean - Closest Observation & 103.254285714286 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 103.485294117647 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 103.511111111111 &  &  \tabularnewline
Number of observations & 68 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96360&T=1

[TABLE]
[ROW][C]Central Tendency - Ungrouped Data[/C][/ROW]
[ROW][C]Measure[/C][C]Value[/C][C]S.E.[/C][C]Value/S.E.[/C][/ROW]
[ROW][C]Arithmetic Mean[/C][C]103.170588235294[/C][C]1.20661961658906[/C][C]85.5038214337527[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]102.687720580833[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]102.195149889976[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]103.642258017948[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 22 )[/C][C]103.142647058824[/C][C]1.18843992177051[/C][C]86.7882718927548[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 22 )[/C][C]103.180882352941[/C][C]1.16003325872090[/C][C]88.9464862987742[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 22 )[/C][C]103.211764705882[/C][C]1.15130290244834[/C][C]89.6477933707924[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 22 )[/C][C]103.194117647059[/C][C]1.14578833762218[/C][C]90.0638575718221[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 22 )[/C][C]103.348529411765[/C][C]1.10496225418523[/C][C]93.5312758606144[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 22 )[/C][C]103.330882352941[/C][C]1.08876305630275[/C][C]94.90667574985[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 22 )[/C][C]103.505882352941[/C][C]1.04868721468543[/C][C]98.7004331734787[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 22 )[/C][C]103.576470588235[/C][C]1.02818514653411[/C][C]100.737178452129[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 22 )[/C][C]103.483823529412[/C][C]1.0124371674195[/C][C]102.212588454424[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 22 )[/C][C]103.557352941176[/C][C]0.99008765093063[/C][C]104.594126432986[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 22 )[/C][C]103.557352941176[/C][C]0.952857898435739[/C][C]108.680793968525[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 22 )[/C][C]103.610294117647[/C][C]0.91059546867767[/C][C]113.783010877603[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 22 )[/C][C]103.629411764706[/C][C]0.901630215154422[/C][C]114.935602226859[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 22 )[/C][C]103.629411764706[/C][C]0.88240795848376[/C][C]117.439343977328[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 22 )[/C][C]103.717647058824[/C][C]0.862294092881539[/C][C]120.281059461081[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 22 )[/C][C]103.717647058824[/C][C]0.840765937996706[/C][C]123.360905064674[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 22 )[/C][C]103.592647058824[/C][C]0.798952112699262[/C][C]129.660646003971[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 22 )[/C][C]103.592647058824[/C][C]0.783169973311035[/C][C]132.273517357747[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 22 )[/C][C]103.397058823529[/C][C]0.745866486427765[/C][C]138.626765922594[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 22 )[/C][C]103.602941176471[/C][C]0.647813132843446[/C][C]159.927201107712[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 22 )[/C][C]103.757352941176[/C][C]0.617616407743162[/C][C]167.996432154899[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 22 )[/C][C]103.886764705882[/C][C]0.554947831556828[/C][C]187.200956195184[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 22 )[/C][C]103.216666666667[/C][C]1.15946813490771[/C][C]89.0207014398741[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 22 )[/C][C]103.2953125[/C][C]1.12456435499675[/C][C]91.8536249535476[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 22 )[/C][C]103.358064516129[/C][C]1.10074622154561[/C][C]93.898177884271[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 22 )[/C][C]103.413333333333[/C][C]1.07570097147751[/C][C]96.1357627029857[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 22 )[/C][C]103.477586206897[/C][C]1.04698178573936[/C][C]98.8341799411747[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 22 )[/C][C]103.508928571429[/C][C]1.02500008484546[/C][C]100.984312198407[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 22 )[/C][C]103.546296296296[/C][C]1.00221527152351[/C][C]103.317420157539[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 22 )[/C][C]103.553846153846[/C][C]0.984336074636877[/C][C]105.201718012872[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 22 )[/C][C]103.55[/C][C]0.966522273991887[/C][C]107.136692848601[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 22 )[/C][C]103.560416666667[/C][C]0.947204451479136[/C][C]109.332696341269[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 22 )[/C][C]103.560869565217[/C][C]0.927275778649608[/C][C]111.682923192530[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 22 )[/C][C]103.561363636364[/C][C]0.90966861929213[/C][C]113.845153542783[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 22 )[/C][C]103.554761904762[/C][C]0.895615869708537[/C][C]115.624081045440[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 22 )[/C][C]103.545[/C][C]0.877999985398049[/C][C]117.932803783655[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 22 )[/C][C]103.534210526316[/C][C]0.857999561617178[/C][C]120.669304691919[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 22 )[/C][C]103.511111111111[/C][C]0.834777584462042[/C][C]123.998431483779[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 22 )[/C][C]103.485294117647[/C][C]0.807398193147852[/C][C]128.171322398162[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 22 )[/C][C]103.471875[/C][C]0.7798655071058[/C][C]132.679127435703[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 22 )[/C][C]103.456666666667[/C][C]0.743967051138743[/C][C]139.060817960032[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 22 )[/C][C]103.464285714286[/C][C]0.702851604486288[/C][C]147.206444509588[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 22 )[/C][C]103.446153846154[/C][C]0.675351322116144[/C][C]153.173837761975[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 22 )[/C][C]103.404166666667[/C][C]0.641936584486673[/C][C]161.081591492958[/C][/ROW]
[ROW][C]Median[/C][C]102.95[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]101.65[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]103.254285714286[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]103.485294117647[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]103.254285714286[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]103.485294117647[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]103.485294117647[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]103.254285714286[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]103.485294117647[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]103.511111111111[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]68[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96360&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96360&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean103.1705882352941.2066196165890685.5038214337527
Geometric Mean102.687720580833
Harmonic Mean102.195149889976
Quadratic Mean103.642258017948
Winsorized Mean ( 1 / 22 )103.1426470588241.1884399217705186.7882718927548
Winsorized Mean ( 2 / 22 )103.1808823529411.1600332587209088.9464862987742
Winsorized Mean ( 3 / 22 )103.2117647058821.1513029024483489.6477933707924
Winsorized Mean ( 4 / 22 )103.1941176470591.1457883376221890.0638575718221
Winsorized Mean ( 5 / 22 )103.3485294117651.1049622541852393.5312758606144
Winsorized Mean ( 6 / 22 )103.3308823529411.0887630563027594.90667574985
Winsorized Mean ( 7 / 22 )103.5058823529411.0486872146854398.7004331734787
Winsorized Mean ( 8 / 22 )103.5764705882351.02818514653411100.737178452129
Winsorized Mean ( 9 / 22 )103.4838235294121.0124371674195102.212588454424
Winsorized Mean ( 10 / 22 )103.5573529411760.99008765093063104.594126432986
Winsorized Mean ( 11 / 22 )103.5573529411760.952857898435739108.680793968525
Winsorized Mean ( 12 / 22 )103.6102941176470.91059546867767113.783010877603
Winsorized Mean ( 13 / 22 )103.6294117647060.901630215154422114.935602226859
Winsorized Mean ( 14 / 22 )103.6294117647060.88240795848376117.439343977328
Winsorized Mean ( 15 / 22 )103.7176470588240.862294092881539120.281059461081
Winsorized Mean ( 16 / 22 )103.7176470588240.840765937996706123.360905064674
Winsorized Mean ( 17 / 22 )103.5926470588240.798952112699262129.660646003971
Winsorized Mean ( 18 / 22 )103.5926470588240.783169973311035132.273517357747
Winsorized Mean ( 19 / 22 )103.3970588235290.745866486427765138.626765922594
Winsorized Mean ( 20 / 22 )103.6029411764710.647813132843446159.927201107712
Winsorized Mean ( 21 / 22 )103.7573529411760.617616407743162167.996432154899
Winsorized Mean ( 22 / 22 )103.8867647058820.554947831556828187.200956195184
Trimmed Mean ( 1 / 22 )103.2166666666671.1594681349077189.0207014398741
Trimmed Mean ( 2 / 22 )103.29531251.1245643549967591.8536249535476
Trimmed Mean ( 3 / 22 )103.3580645161291.1007462215456193.898177884271
Trimmed Mean ( 4 / 22 )103.4133333333331.0757009714775196.1357627029857
Trimmed Mean ( 5 / 22 )103.4775862068971.0469817857393698.8341799411747
Trimmed Mean ( 6 / 22 )103.5089285714291.02500008484546100.984312198407
Trimmed Mean ( 7 / 22 )103.5462962962961.00221527152351103.317420157539
Trimmed Mean ( 8 / 22 )103.5538461538460.984336074636877105.201718012872
Trimmed Mean ( 9 / 22 )103.550.966522273991887107.136692848601
Trimmed Mean ( 10 / 22 )103.5604166666670.947204451479136109.332696341269
Trimmed Mean ( 11 / 22 )103.5608695652170.927275778649608111.682923192530
Trimmed Mean ( 12 / 22 )103.5613636363640.90966861929213113.845153542783
Trimmed Mean ( 13 / 22 )103.5547619047620.895615869708537115.624081045440
Trimmed Mean ( 14 / 22 )103.5450.877999985398049117.932803783655
Trimmed Mean ( 15 / 22 )103.5342105263160.857999561617178120.669304691919
Trimmed Mean ( 16 / 22 )103.5111111111110.834777584462042123.998431483779
Trimmed Mean ( 17 / 22 )103.4852941176470.807398193147852128.171322398162
Trimmed Mean ( 18 / 22 )103.4718750.7798655071058132.679127435703
Trimmed Mean ( 19 / 22 )103.4566666666670.743967051138743139.060817960032
Trimmed Mean ( 20 / 22 )103.4642857142860.702851604486288147.206444509588
Trimmed Mean ( 21 / 22 )103.4461538461540.675351322116144153.173837761975
Trimmed Mean ( 22 / 22 )103.4041666666670.641936584486673161.081591492958
Median102.95
Midrange101.65
Midmean - Weighted Average at Xnp103.254285714286
Midmean - Weighted Average at X(n+1)p103.485294117647
Midmean - Empirical Distribution Function103.254285714286
Midmean - Empirical Distribution Function - Averaging103.485294117647
Midmean - Empirical Distribution Function - Interpolation103.485294117647
Midmean - Closest Observation103.254285714286
Midmean - True Basic - Statistics Graphics Toolkit103.485294117647
Midmean - MS Excel (old versions)103.511111111111
Number of observations68



Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
geomean <- function(x) {
return(exp(mean(log(x))))
}
harmean <- function(x) {
return(1/mean(1/x))
}
quamean <- function(x) {
return(sqrt(mean(x*x)))
}
winmean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
win <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
win[j,1] <- (j*x[j+1]+sum(x[(j+1):(n-j)])+j*x[n-j])/n
win[j,2] <- sd(c(rep(x[j+1],j),x[(j+1):(n-j)],rep(x[n-j],j)))/sqrtn
}
return(win)
}
trimean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
tri <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
tri[j,1] <- mean(x,trim=j/n)
tri[j,2] <- sd(x[(j+1):(n-j)]) / sqrt(n-j*2)
}
return(tri)
}
midrange <- function(x) {
return((max(x)+min(x))/2)
}
q1 <- function(data,n,p,i,f) {
np <- n*p;
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q2 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q3 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
q4 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- (data[i]+data[i+1])/2
} else {
qvalue <- data[i+1]
}
}
q5 <- function(data,n,p,i,f) {
np <- (n-1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i+1]
} else {
qvalue <- data[i+1] + f*(data[i+2]-data[i+1])
}
}
q6 <- function(data,n,p,i,f) {
np <- n*p+0.5
i <<- floor(np)
f <<- np - i
qvalue <- data[i]
}
q7 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- f*data[i] + (1-f)*data[i+1]
}
}
q8 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
if (f == 0.5) {
qvalue <- (data[i]+data[i+1])/2
} else {
if (f < 0.5) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
}
}
midmean <- function(x,def) {
x <-sort(x[!is.na(x)])
n<-length(x)
if (def==1) {
qvalue1 <- q1(x,n,0.25,i,f)
qvalue3 <- q1(x,n,0.75,i,f)
}
if (def==2) {
qvalue1 <- q2(x,n,0.25,i,f)
qvalue3 <- q2(x,n,0.75,i,f)
}
if (def==3) {
qvalue1 <- q3(x,n,0.25,i,f)
qvalue3 <- q3(x,n,0.75,i,f)
}
if (def==4) {
qvalue1 <- q4(x,n,0.25,i,f)
qvalue3 <- q4(x,n,0.75,i,f)
}
if (def==5) {
qvalue1 <- q5(x,n,0.25,i,f)
qvalue3 <- q5(x,n,0.75,i,f)
}
if (def==6) {
qvalue1 <- q6(x,n,0.25,i,f)
qvalue3 <- q6(x,n,0.75,i,f)
}
if (def==7) {
qvalue1 <- q7(x,n,0.25,i,f)
qvalue3 <- q7(x,n,0.75,i,f)
}
if (def==8) {
qvalue1 <- q8(x,n,0.25,i,f)
qvalue3 <- q8(x,n,0.75,i,f)
}
midm <- 0
myn <- 0
roundno4 <- round(n/4)
round3no4 <- round(3*n/4)
for (i in 1:n) {
if ((x[i]>=qvalue1) & (x[i]<=qvalue3)){
midm = midm + x[i]
myn = myn + 1
}
}
midm = midm / myn
return(midm)
}
(arm <- mean(x))
sqrtn <- sqrt(length(x))
(armse <- sd(x) / sqrtn)
(armose <- arm / armse)
(geo <- geomean(x))
(har <- harmean(x))
(qua <- quamean(x))
(win <- winmean(x))
(tri <- trimean(x))
(midr <- midrange(x))
midm <- array(NA,dim=8)
for (j in 1:8) midm[j] <- midmean(x,j)
midm
bitmap(file='test1.png')
lb <- win[,1] - 2*win[,2]
ub <- win[,1] + 2*win[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(win[,1],type='b',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(win[,1],type='l',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
bitmap(file='test2.png')
lb <- tri[,1] - 2*tri[,2]
ub <- tri[,1] + 2*tri[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(tri[,1],type='b',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(tri[,1],type='l',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Central Tendency - Ungrouped Data',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Measure',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.element(a,'S.E.',header=TRUE)
a<-table.element(a,'Value/S.E.',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE)
a<-table.element(a,arm)
a<-table.element(a,hyperlink('arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean'))
a<-table.element(a,armose)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE)
a<-table.element(a,geo)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE)
a<-table.element(a,har)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE)
a<-table.element(a,qua)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
for (j in 1:length(win[,1])) {
a<-table.row.start(a)
mylabel <- paste('Winsorized Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(win[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a,hyperlink('winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE)
a<-table.element(a,win[j,1])
a<-table.element(a,win[j,2])
a<-table.element(a,win[j,1]/win[j,2])
a<-table.row.end(a)
}
for (j in 1:length(tri[,1])) {
a<-table.row.start(a)
mylabel <- paste('Trimmed Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(tri[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a,hyperlink('arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE)
a<-table.element(a,tri[j,1])
a<-table.element(a,tri[j,2])
a<-table.element(a,tri[j,1]/tri[j,2])
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,hyperlink('median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE)
a<-table.element(a,median(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE)
a<-table.element(a,midr)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_1.htm','Weighted Average at Xnp',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[1])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[2])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_3.htm','Empirical Distribution Function',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[3])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[4])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[5])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_6.htm','Closest Observation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[6])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[7])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_8.htm','MS Excel (old versions)',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[8])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of observations',header=TRUE)
a<-table.element(a,length(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')